code: def test_learning_process(self):
      inet = algorithms.Instar(
          step=1, verbose=False, **self.default_properties
      )
  
      inet.train(X, epochs=10)
  
      test_input = np.array([[0, 1, -1, -1]])
      self.assertEqual(inet.predict(test_input), 1)
  
      np.testing.assert_array_equal(
          inet.weight, np.array([[3, 1, -1, -1]]).T
      )
  
file_path: neupy/tests/algorithms/associative/test_instar.py
imports: import numpy
  from neupy import algorithms
  from base import BaseTestCase
label_desc: Use image node_id 2 for calling the HebbRuleTestCase obj's underlying member method code with example usage: obj.test_learning_process() without return types